scholarly journals Progressive simplification of polygonal curves

2020 ◽  
Vol 88 ◽  
pp. 101620
Author(s):  
Kevin Buchin ◽  
Maximilian Konzack ◽  
Wim Reddingius
Keyword(s):  
Author(s):  
Anne Driemel ◽  
André Nusser ◽  
Jeff M. Phillips ◽  
Ioannis Psarros

AbstractThe Vapnik–Chervonenkis dimension provides a notion of complexity for systems of sets. If the VC dimension is small, then knowing this can drastically simplify fundamental computational tasks such as classification, range counting, and density estimation through the use of sampling bounds. We analyze set systems where the ground set X is a set of polygonal curves in $$\mathbb {R}^d$$ R d and the sets $$\mathcal {R}$$ R are metric balls defined by curve similarity metrics, such as the Fréchet distance and the Hausdorff distance, as well as their discrete counterparts. We derive upper and lower bounds on the VC dimension that imply useful sampling bounds in the setting that the number of curves is large, but the complexity of the individual curves is small. Our upper and lower bounds are either near-quadratic or near-linear in the complexity of the curves that define the ranges and they are logarithmic in the complexity of the curves that define the ground set.


2019 ◽  
Vol 29 (02) ◽  
pp. 161-187
Author(s):  
Joachim Gudmundsson ◽  
Majid Mirzanezhad ◽  
Ali Mohades ◽  
Carola Wenk

Computing the Fréchet distance between two polygonal curves takes roughly quadratic time. In this paper, we show that for a special class of curves the Fréchet distance computations become easier. Let [Formula: see text] and [Formula: see text] be two polygonal curves in [Formula: see text] with [Formula: see text] and [Formula: see text] vertices, respectively. We prove four results for the case when all edges of both curves are long compared to the Fréchet distance between them: (1) a linear-time algorithm for deciding the Fréchet distance between two curves, (2) an algorithm that computes the Fréchet distance in [Formula: see text] time, (3) a linear-time [Formula: see text]-approximation algorithm, and (4) a data structure that supports [Formula: see text]-time decision queries, where [Formula: see text] is the number of vertices of the query curve and [Formula: see text] the number of vertices of the preprocessed curve.


2016 ◽  
Vol 26 (01) ◽  
pp. 33-52 ◽  
Author(s):  
Christian Scheffer

We study a modified version of the partial Fréchet similarity that is motivated by real world applications, e.g. the analysis of spectroscopic data in the context of astroinformatics and the analysis of birds’ migration trajectories. In those practical applications of curve matching it is often necessary to ignore outliers while dissimilarities regarding individual directions should be weighted by individual costs. We enable both by computing the partial Fréchet similarity between polygonal curves w.r.t. a non-uniform metric. In particular, we measure distances by a function [Formula: see text] that is induced by a set of weighted vectors. We discuss the approximation quality of [Formula: see text] regarding any [Formula: see text] metric and present a polynomial time algorithm for computing an exact solution of the resulting modified partial Fréchet similarity.


2016 ◽  
Vol 26 (01) ◽  
pp. 53-66 ◽  
Author(s):  
M. I. Schlesinger ◽  
E. V. Vodolazskiy ◽  
V. M. Yakovenko

The article analyzes similarity of closed polygonal curves with respect to the Fréchet metric, which is stronger than the well-known Hausdorff metric and therefore is more appropriate in some applications. An algorithm is described that determines whether the Fréchet distance between two closed polygonal curves with [Formula: see text] and [Formula: see text] vertices is less than a given number [Formula: see text]. The algorithm takes [Formula: see text] time whereas the previously known algorithms take [Formula: see text] time.


Author(s):  
Philip Smith ◽  
Eleni Panagiotou

Abstract Biopolymers, like chromatin, are often confined in small volumes. Confinement has a great effect on polymer conformations, including polymer entanglement. Polymer chains and other filamentous structures can be represented by polygonal curves in 3-space. In this manuscript, we examine the topological complexity of polygonal chains in 3-space and in confinement as a function of their length. We model polygonal chains by equilateral random walks in 3-space and by uniform random walks in confinement. For the topological characterization, we use the second Vassiliev measure. This is an integer topological invariant for polygons and a continuous functions over the real numbers, as a function of the chain coordinates for open polygonal chains. For uniform random walks in confined space, we prove that the average value of the Vassiliev measure in the space of configurations increases as $O(n^2)$ with the length of the walks or polygons. We verify this result numerically and our numerical results also show that the mean value of the second Vassiliev measure of equilateral random walks in 3-space increases as $O(n)$. These results reveal the rate at which knotting of open curves and not simply entanglement are affected by confinement.


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